Background Compressive sensing (CS) is a transformative sampling technique that allows sparse signals to be sampled in compressed form at a rate much lower than the Nyquist rate. In particular, end-to-end data-driven image compressive sensing reconstruction (EDCSR) frameworks achieve state-of-the-art reconstruction performance in terms of speed and...

CSVideoNet: A Real-time End-to-end Learning Framework for High-frame-rate Video Compressive Sensing Background High-frame-rate cameras are capable of capturing videos at frame rates over 100 frames per second (fps). These devices were originally developed to characterize rapid events. Some high-frame-rate cameras can record high resolution still images...

Background Compressive sensing (CS) is a transformative sampling technique that allows sparse signals to be sampled in compressed form at a rate much lower than the Nyquist rate. However, conventional CS reconstruction techniques, based on either convex optimization or iterative methods, come with three drawbacks in imaging applications: (1) High complexity...